Use Cases for Conversational AI in Retail show how employees, clients, and partners may easily communicate within your company.
The only constant in retail is change. Businesses have dealt with more change in the last two years than in the previous two decades. Record-high shipping costs, diminishing returns on online advertising, and a massive increase in the number of channels businesses sell are shaking up the way you shop, sell, and ship.
The retail industry is perhaps the most widespread use of conversational AI. Companies like Amazon, eBay, AliExpress, and many others have fundamentally changed the way customers interact with retailers. According to Shopify, 53% of brands invest in tools that allow them to sell anywhere. This shift in consumer behavior, combined with the increased competition from digitally native brands moving into retail, means it’s not enough to use the retail store for acquisition alone. Retailers must build relationships and experiences with their customers that only omnichannel commerce can offer.
With the help of a conversational AI platform, customers can interact with your company, ask questions, get advice and personalized recommendations, read reviews, and complete purchases. These experiences can be delivered through virtual AI assistants, human agents, or a mix of the two. Virtual AI assistants can minimize human workload, improve quality, and significantly cut costs by enabling seamless automation.
Customer service representatives are human beings, and they can’t complete all tasks accurately and quickly around the clock. However, many customers hold this expectation of retailers. Fortunately, conversational AI provides accurate, real-time responses to any questions about inventory supply, product recommendations, prices, offer durations, etc. Plus, as virtual AI assistants can operate 24/7, customers always get the support they need–without overwhelming human assistants.
Conversational AI can comprehend and assess the intent, context, and question of the users, independent of how it is stated, thanks to Natural Language Processing (NLP). With each encounter, conversational AI may provide better and more precise answers by leveraging Machine Learning (ML), all without the need for human participation. Using these technologies, conversational AI can respond appropriately to complex queries in a human-like manner.
Now, let's look at the top 6 use cases of conversational AI in retail.
Customers who want to research online services find virtual AI assistants highly useful. Customers want to know how the objects they plan to purchase will feel and appear in real life, which leads most individuals to buy them offline, making it a noteworthy issue for online retail stores. As such, it’s no wonder that 54% of consumers say that, over the next year, they’re likely to look at a product online and buy it in-store, and 53% are likely to look at a product in-store and buy it online.
Having a virtual AI assistant provides customers with verbal clarifications and guidance while they shop, which will energize and improve their online experience. It will tie up the bond between a brand and its customers. As such, customers will be more inclined to complete the entire shopping process online–and be more satisfied with their purchase.
As customers usually get in touch with retailers for a broad range of issues or inquiries, having a helpful and efficient customer service department is crucial for retail and logistics businesses. Incorporating conversational AI within your customer service department can automate simple to moderate activities like:
Conversational AI analytics and metrics help businesses better understand their customers so they can improve their shopping journey. Additionally, virtual AI assistants can easily integrate with your other retail business processing systems and enable 24/7 availability for fast problem resolution. Investing in conversational AI for your customer service department equips your business with a powerful tool for customer experience analysis and boosts your client retention rate.
Onboarding procedures for new employees can also benefit from conversational AI. This is especially helpful to ensure that new hires are receiving all the relevant knowledge about their position and that they will rely less on their more seasoned colleagues or management for assistance. Not only does this better equip your new hires for work, but it accelerates the onboarding process, saving you time and money.
Employees can use the conversational AI platform to ask questions, find resources, and interact with support as needed. The traditional onboarding process, which typically lasts for a week, may not be enough for a new team member to get acquainted with the job, the workplace, and the company culture. Fortunately, conversational AI enables a fast yet effective onboarding process by supporting the trainee with check-ins, tips, tricks, and training sessions to help him find his place and workflow in no time.
Demand forecasting is a crucial component of the retail and logistics industry. After all, how can you effectively serve customers if you aren’t aware of their needs and changing demands? Unfortunately, obtaining the right data for demand forecasting can be challenging, yet without it, you can’t make an accurate forecast.
Fortunately, conversational AI platforms are capable of analyzing consumer conversations and interactions. Virtual AI assistants can analyze and store data regarding customer demands, requests, and frustrations–all of which can be used to predict demand in the future. Upon this analysis, the conversational AI solution will allow companies to extract customer data to use for demand forecasting.
This information will help retailers prepare their warehouses and trucks to accommodate demand, as well as restock certain products and make necessary adjustments to satisfy customer demand.
Machines are becoming more intelligent, businesses are using data, and online customers want a customized experience. However, making sense of what's happening at your store due to all of this is more difficult than ever. That being said, to customize the shopping experience for customers, as well as generate new leads, companies must determine a way to effectively listen to their demands.
Fortunately, in the same way that conversational AI can analyze customer interactions for demand forecasting, this data can also be used for personalization. The conversational AI solution will collect data on customer demands and feedback to help companies personalize their offerings, marketing campaigns, and products.
This data can even be used to create predefined metrics for customer qualification, making it easier for retailers to find and identify customers. The application of conversational AI-enabled consumer data will help retailers offer products that their customers actually want, as well as help them generate and qualify new leads.
GET THE GUIDE: CONVERSATIONAL AI FOR RETAIL
Hyper-automation, often known as intelligent business process automation, refers to the end-to-end automation of processes utilizing a combination of robotic process automation (RPA), process mining, and other technologies. Businesses can automate many back-office processes using these technologies.
Used in tandem with RPA, Conversational AI can help companies automate time-consuming administrative tasks such as tracking and scheduling, generating reports, and emailing customers. The conversational AI solution is capable of performing these tasks in a human-like manner, triggering automation through RPA technologies. The integration of these technologies will help companies offer a personalized and intelligent yet fast and effective customer experience.
Conversational AI is no longer a technology of the future but one that is ready to be implemented and leveraged today. The technology is now entering several significant sectors, including retail, where it promises to bring cost-efficiency and help retailers deliver an improved consumer experience.
If you’re interested in learning more about DRUID AI for retail, we’ve got you covered!
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